{"id":"W3182493091","doi":"10.1136/bmjmilitary-2021-001912","title":"3D-printed laryngoscope for military austere environments","year":2021,"lang":"en","type":"article","venue":"BMJ Military Health","topic":"Airway Management and Intubation Techniques","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"General Dynamics (Canada)","funders":"","keywords":"3D printing; 3d printed; Engineering; Manufacturing engineering; Computer science; Mechanical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005351535,0.0004663268,0.0003217238,0.0008213569,0.000390211,0.001084215,0.0007982175,0.001399362,0.0200075],"category_scores_gemma":[0.001803359,0.0002818362,0.0008264407,0.0003022035,0.0004518707,0.0009622492,0.0009753155,0.001348271,0.008154548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002676412,"about_ca_system_score_gemma":0.0004528485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004781692,"about_ca_topic_score_gemma":0.0009764978,"domain_scores_codex":[0.9993318,0.00007142418,0.00004760581,0.00005161593,0.0004735975,0.00002398645],"domain_scores_gemma":[0.9992605,0.0002635642,0.0001023076,0.000112048,0.0001959837,0.00006564725],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003377399,0.00012283,0.00229309,0.002252562,0.0000633227,0.005261164,0.0003965958,0.002946165,0.2670579,0.006154445,0.07109616,0.642018],"study_design_scores_gemma":[0.00007817862,0.0008453475,0.009731074,0.0007399214,0.000140628,0.06694317,0.0001891112,0.01221972,0.1472689,0.004960323,0.7566668,0.000216737],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.064804,0.08448575,0.6585495,0.009264062,0.01129847,0.0005357705,0.001982308,0.01353497,0.1555452],"genre_scores_gemma":[0.4365588,0.03949363,0.3808202,0.004741075,0.002930739,0.0004511439,0.001559359,0.001973005,0.1314721],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0200075,"threshold_uncertainty_score":0.06693172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0347450867618664,"score_gpt":0.3574246241147985,"score_spread":0.3226795373529321,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}